Hospital capacity data

The covid19sf package provides two datasets focusing on the overall hospital capacity and patients status in San Francisco hospitals:

• covid19sf_hospital - a daily snapshot of the hospital capacity
• covid19sf_hospitalizations - a daily snapshot of the patients status

Hospital Capacity

The covid19sf_hospital dataset provides a daily snapshot of the San Francisco hospital capacity by bed type and status with the following variables:

• bed_type - number of hospital beds available by department type:
  • Acute Care
  • Intensive Care
  • Acute Care Surge
  • Intensive Care Surge
• status - the department corresponding bed status:
  • Available
  • COVID-19 (Confirmed & Suspected)
  • Other Patients

data(covid19sf_hospital)

head(covid19sf_hospital)
#>                 hospital       date             bed_type    status count
#> 1 All SF Acute Hospitals 2020-07-22 Intensive Care Surge Available   309
#> 2 All SF Acute Hospitals 2021-07-18 Intensive Care Surge Available   298
#> 3 All SF Acute Hospitals 2020-07-22     Acute Care Surge Available   406
#> 4 All SF Acute Hospitals 2021-07-18           Acute Care Available   487
#> 5 All SF Acute Hospitals 2021-07-18     Acute Care Surge Available   247
#> 6 All SF Acute Hospitals 2021-07-18       Intensive Care Available   123

Let’s summarise the hospital status as of the most recent date available on the dataset:

library(dplyr)

covid19sf_hospital %>%
  filter(date == max(date)) %>%
  group_by(bed_type, status) %>%
  summarise(total = sum(count))
#> # A tibble: 10 × 3
#> # Groups:   bed_type [4]
#>    bed_type             status                           total
#>    <chr>                <chr>                            <int>
#>  1 Acute Care           Available                          487
#>  2 Acute Care           COVID-19 (Confirmed & Suspected)    31
#>  3 Acute Care           Other Patients                    1098
#>  4 Acute Care Surge     Available                          247
#>  5 Acute Care Surge     Occupied Surge                       0
#>  6 Intensive Care       Available                          123
#>  7 Intensive Care       COVID-19 (Confirmed & Suspected)    15
#>  8 Intensive Care       Other Patients                     148
#>  9 Intensive Care Surge Available                          298
#> 10 Intensive Care Surge Occupied Surge                       0

library(plotly)

covid19sf_hospital %>%
  filter(bed_type == "Acute Care") %>%
  mutate(status = factor(status, levels = c("Other Patients", "COVID-19 (Confirmed & Suspected)", "Available"))) %>%
  plot_ly(x = ~ date,
          y = ~ count,
          type = 'scatter', 
          mode = 'none', 
          color = ~status,
          stackgroup = 'one') %>%
    layout(title = "SF Acute Hospitals - Acute Care Bed Count",
          legend = list(x = 0.05, y = 0.95),
         yaxis = list(title = "Number of Beds", tickformat = ".0f"),
         xaxis = list(title = "Source: San Francisco Department of Public Health"),
         hovermode = "compare")

covid19sf_hospital %>%
  filter(bed_type == "Intensive Care") %>%
  mutate(status = factor(status, levels = c("Other Patients", "COVID-19 (Confirmed & Suspected)", "Available"))) %>%
  plot_ly(x = ~ date,
          y = ~ count,
          type = 'scatter', 
          mode = 'none', 
          color = ~status,
          stackgroup = 'one') %>%
    layout(title = "SF Acute Hospitals - Intensive Care Bed Count",
          legend = list(x = 0.05, y = 1),
         yaxis = list(title = "Number of Beds", tickformat = ".0f"),
         xaxis = list(title = "Source: San Francisco Department of Public Health"),
         hovermode = "compare")

Covid19 Hospitalizations

The covid19sf_hospitalizations provides daily snapshot of the number of patients in San Francisco hospitals by hospitalization unit and Covid19 status using the following variables:

• dphcategory - the hospital unit type, either ICU (intensive care unit) or Med/Surg (acute care).
• covidstatus - the Covid19 status, either COVID+ (confirmed cases) or PUI (patient under investigation)

The below example summarised the hospitalizations status as of the most recent date in the data:

data(covid19sf_hospitalizations)

covid19sf_hospitalizations %>%
  filter(reportdate == max(reportdate)) %>%
  group_by(dphcategory, covidstatus) %>%
  summarise(total = sum(patientcount))
#> # A tibble: 4 × 3
#> # Groups:   dphcategory [2]
#>   dphcategory covidstatus total
#>   <chr>       <chr>       <int>
#> 1 ICU         COVID+          9
#> 2 ICU         PUI             0
#> 3 Med/Surg    COVID+         23
#> 4 Med/Surg    PUI             2